An ever-increasing number of relatively cheap, low power wireless data communication services, networks and devices have been made available over the past number of years, promising near wire speed transmission and reliability. Various wireless technologies are described in detail in the 802.11 IEEE Standard, including for example, the IEEE Standard 802.11a (1999) and its updates and amendments, the IEEE Standard 802.11g (2003), 3GPP LTE, as well as the IEEE Standard 802.11n now in the process of being adopted, all of which are collectively incorporated herein fully by reference. These standards have been or are in the process of being commercialized with the promise of 54 Mbps or more effective throughput such as 100 Mbps, making them a strong competitor to traditional wired Ethernet and the more ubiquitous “802.11b” or “WiFi” 11 Mbps mobile wireless transmission standard.
In general, transmission systems compliant with the IEEE 802.11a and 802.11g or “802.11a/g,” 802.16 or 3GPP LTE, as well as the 802.11n standards achieve high data transmission rates using Orthogonal Frequency Division Modulation or OFDM encoded symbols and using quadrature amplitude modulation (QAM) on the OFDM sub-bands. In a general sense, the use of OFDM divides the overall system bandwidth into a number of frequency sub-bands or channels, with each frequency sub-band being associated with a respective sub-carrier upon which data may be modulated. Thus, each frequency sub-band of the OFDM system may be viewed as an independent transmission channel within which to send data, thereby increasing the overall throughput or transmission rate of the communication system.
Transmitters used in the wireless communication systems that are compliant with the 802.11a/802.11g/802.11n standards as well as other standards such as the 3GPP LTE and 802.16a IEEE Standard, typically perform multi-carrier OFDM symbol encoding (which may include error correction encoding and interleaving), convert the encoded symbols into the time domain using Inverse Fast Fourier Transform (IFFT) techniques, and perform digital to analog conversion and conventional radio frequency (RF) upconversion on the signals. These transmitters then transmit the modulated and upconverted signals after appropriate power amplification to one or more receivers, resulting in a relatively high-speed time domain signal with a large peak-to-average ratio (PAR).
Likewise, the receivers used in the wireless communication systems that are compliant with the 802.11a/802.11g/802.11n, 3GPP LTE and 802.16a IEEE standards typically include an RF receiving unit that performs RF downconversion and filtering of the received signals (which may be performed in one or more stages), and a baseband processor unit that processes the OFDM encoded symbols bearing the data of interest. The digital form of each OFDM symbol presented in the frequency domain is recovered after baseband downconverting, conventional analog to digital conversion and Fast Fourier Transformation of the received time domain signal. Thereafter, the baseband processor performs demodulation and frequency domain equalization (FEQ) to recover the transmitted symbols, and these symbols are then processed with an appropriate FEC decoder, e.g. a Viterbi decoder, to estimate or determine the most likely identity of the transmitted symbol. The recovered and recognized stream of symbols is then decoded, which may include deinterleaving and further error correction using any of a number of known error correction techniques, to produce a set of recovered signals corresponding to the original signals transmitted by the transmitter.
To further increase the number of signals which may be propagated in the communication system and/or to compensate for deleterious effects associated with the various propagation paths, and to thereby improve transmission performance, it is known to use multiple transmission and receive antennas within a wireless transmission system. Such a system is commonly referred to as a multiple-input, multiple-output (MIMO) wireless transmission system and is specifically provided for within the 3GPP LTE and the 802.11n IEEE Standard now being adopted. The use of MIMO technology produces significant increases in spectral efficiency, throughput, and link reliability. These benefits generally increase as the number of transmission and receive antennas included in the MIMO system increases.
In particular, in addition to the frequency channels created by the use of OFDM, a MIMO channel formed by the various transmission and receive antennas between a particular transmitter and a particular receiver includes a number of independent spatial channels. A wireless MIMO communication system can provide improved performance (e.g., increased transmission capacity) by utilizing the additional dimensionalities created by these spatial channels for the transmission of additional data. Of course, the spatial channels of a wideband MIMO system may experience different channel conditions (e.g., different fading and multi-path effects) across the overall system bandwidth and may therefore achieve different SNRs at different frequencies (i.e., at the different OFDM frequency sub-bands) of the overall system bandwidth. Consequently, the number of information bits per modulation symbol (i.e., the data rate) that may be transmitted using the different frequency sub-bands of each spatial channel for a particular level of performance may differ from frequency sub-band to frequency sub-band.
In MIMO wireless communication systems, the RF modulated signals transmitted by the transmit antennas may reach the various receive antennas via a number of different propagation paths, the characteristics of which typically change over time due to the phenomena of multi-path and fading. Moreover, the characteristics of the various propagation sub-channels differ or vary based on the frequency of propagation. To compensate for the time varying, frequency selective nature of these propagation effects, and generally to enhance effective encoding and modulation in a MIMO wireless communication system, and improve the overall system throughput, the receiver of the MIMO wireless communication system may periodically develop or collect channel state information (CSI) for the wireless channel between the transmitter and receiver. Generally, the wireless channel comprises a composite channel in which the effects of all combinations of transmit antennas and receive antennas are taken into account. A channel matrix may be created comprising a plurality of complex channel values representing the channel characteristics (for example, the gain, the phase and the SNR of each channel) between each transmit-receive antenna pair. Upon determining the CSI for the composite channel, the receiver may send the CSI, or other information derived from the CSI, back to the transmitter, which may use the CSI or other information derived from the CSI, to precondition or precode the signals transmitted over channel so as to compensate for the varying propagation effects of the channels.
A precoding matrix may be developed which when multiplied with the transmitted signal negates the propagation effects of the channel. However, because the propagation effects of the wireless channel vary over time, a single precoding matrix will only be sufficient to compensate for one set of channel characteristics. Separate precoding matrices must be developed to compensate for different sets of channel characteristics. A plurality of precoding matrices may be derived in advance in order to compensate for a range of different channel conditions. The plurality of precoding matrices may be assembled in a codebook which may be stored in a memory associated with the transmitter. Upon measuring the CSI, the receiver in a MIMO wireless communication system may determine which of the precoding matrices in the codebook is most appropriate to compensate for the measured CSI. The receiver may transmit a precoding matrix index or other identifier back to the transmitter specifying which precoding matrix in the codebook should be used to precode signals to be transmitted over the channel. The transmitter may then precode signals using the specified precoding matrix.
The size of the codebook, i.e. the number of precoding matrices included in the codebook, can have a significant impact on system throughput and overall channel efficiency. With a large codebook having many precoding matrices to choose from, it is possible to select a precoding matrix which closely matches (i.e. counteracts) the measured propagation effects of the channel. By accurately counter-acting the propagation effects of the channel system throughput can be significantly improved. However, a larger codebook requires a larger amount of data to be fed back from the receiver to the transmitter in order to identify a particular precoding matrix to be used for precoding transmitted signals. The additional feedback data required of a large codebook consumes additional channel overhead and has a negative impact on channel efficiency. Under certain conditions, such as a channel with a high SNR, the improved system throughput associated with a large codebook may be worth the cost in added overhead. In other cases, such as a poor quality channel with a low SNR, the improved system throughput, even with a large codebook, may not justify the cost in increased channel overhead. When designing a codebook for a MIMO wireless communication system there is a tension between creating a large codebook with the possibility of significant improvements in system throughput under favorable conditions and creating a smaller codebook which will consume less channel overhead, and will not diminish system throughput when channel conditions are less than ideal.